Teaching and Resources
GRADUATE
Identity Politics PP 333 (Fall 2023)
Computational Tools for Social Science SPE 489 (Fall 2023)
Visualizing Data SPE 487 (Spring 2023)
American Political Behavior PP 302 (Spring 2022, Spring 2023)
Survey Research PP484 (Fall 2022)
UNDERGRADUATE
Teaching Experience: Instructor
Graduate Bootcamp in R Statistical Programming (2016-2019)
PS6: Intro to Data Analysis (Summer 2018)
Cluster 60A: Intro to Data Analysis — Public Opinion in the 1960s (Spring 2019)
Teaching Experience: Teaching Assistant
Political Communications, UCLA (Fall 2018; Winter 2018)
American Politics, UW (Fall 2014; Winter 2014; Spring 2015)
RESOURCES
Skills Building in Graduate School
My talk to CGU graduate students: Skills Building in Graduate School
On being a successful graduate student
From my experience, a key factor distinguishing between successful and less successful grad students, is the willingness to put oneself "out there" and ask for feedback (on memos, drafts) early and regularly.
— Guy Grossman (he/him) (@guygrossman) September 9, 2022
Arthur Sprirling Advice on Being a Graduate Student
Michael J. Nelson: On Reading Papers like a Prof
On Writing Academic Papers (cont.)
On Navigating an R&R from APSR editors
Free student access to programming classes
Experimental Methods Resources
Creating Realistic Stimuli with Chrome Developer Tools
Recent research on best practices in experimental political science
Public Data Sources Political Data
Polling, Voting, and Census Data Resources
Presidential, Senatorial, & Gubernatorial Elections in the U.S. Counties, 1872-2020
Social Explorer for Aggregated Census Data
Melange of different poli sci datasets from Joseph Coll
Text as Data
Diff in Diff Methods
Readings and Code for Diff in Diff Methods
Checklist for DiD Practitioners (see Table 1)
Shapefiles and Spatial Data
Historic Shapefile Boundaries (state, county, congressional district, and zip code) 1629 - 2000
Bridging Census Tracts Over time
Spatial data for R (free book)
MRP Guides and Software
Guide by Jonathan Kastellec (w/data)
AAPOR Presentation by Doug Rivers
MRP With rstanarm by Lauren Kennedy and Johan Gabry
MRP using brms and tidybayes by Tim Mastny
Measuring Attitudes – Multilevel Modeling with Post-Stratification book chapter by Leeman and Wasserfallen // Code Guide to Accompany Leeman and Wasserfallen Chapter
An Introduction to Multilevel Regression and Post-Stratification for Estimating Constituency Opinion // Replication Data